Learning based metric determination and clustering for service routing
US10715668B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 27, 2018 |
| Grant date | Jul 14, 2020 |
| Priority date | — |
| Expiry date | Feb 27, 2038 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04M2203/408
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques are described for generating metric(s) that predict survey score(s) for a service session. Model(s) may be trained, through supervised or unsupervised machine learning, using training data such as communications from previous service sessions between service representative(s) and individual(s), and survey scores provided by the serviced individual to rate the session on one or more criteria (e.g., survey questions). The model(s) may be trained to output, based on an input session record, metric(s) that each correspond to a survey score that would have been provided by the individual had they completed the survey. The model may be a concatenated model that combines a language model output from a language classifier recurrent neural network, and an acoustic model output from an acoustic feature layer convolutional neural network. Individuals can be clustered according to the metric(s) and/or other factors, and the cluster(s) can be employed for routing incoming service requests.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.